Radiography最新文献

{"title":"Impact of walking on knee articular cartilage T2 values estimated with a dictionary-based approach - A pilot study","authors":"J.M. Coelho ,&nbsp;T.T. Fernandes ,&nbsp;S.M. Alves ,&nbsp;R.G. Nunes ,&nbsp;L. Nogueira ,&nbsp;A. Oliveira","doi":"10.1016/j.radi.2024.10.018","DOIUrl":"10.1016/j.radi.2024.10.018","url":null,"abstract":"<div><h3>Introduction</h3><div>Walking is crucial for knee articular cartilage (KAC) health. Routine MRI sequences lack sensitivity for early cartilage changes, and the use of parametric T₂ maps to study the effect of walking on KAC composition is limited. This study aimed to evaluate if quantitative T2 maps using an Echo Modulation Curve (EMC) matching algorithm can detect KAC T2 variations due to water content changes after walking.</div></div><div><h3>Methods</h3><div>Seven asymptomatic volunteers (3 females, 4 males, mean age 28.3 years) without knee pathologies participated. Sagittal knee MRI scans were performed before and after a 9-min treadmill walk using a Modified Bruce protocol. T2-weighted Multi-Echo Spin-Echo KAC images were acquired at 3T. Tibiofemoral cartilage was segmented semi-automatically on three slices per knee, defining 39 KAC samples. Quantitative T2 maps were created using a dictionary-matching algorithm. Paired t-tests assessed exercise impact on KAC T2 values, independent t-tests compared group differences, and Friedman test with Bonferroni correction evaluated regional T2 changes.</div></div><div><h3>Results</h3><div>Walking increased KAC T2 values (mean difference (md) 0.61 ± 1.71 ms; p = 0.016). Significant differences were observed in “normal” BMI group (md 0.69 ± 1.27 ms; p = 0.021). Regional analysis revealed significant differences in medial femur in males (md 0.9 ± 2.1 ms; p = 0.049) and lateral tibia in females (md 1.4 ± 2.5 ms; p = 0.046). The medial tibia showed significant differences across sub-regions (p = 0.026).</div></div><div><h3>Conclusion</h3><div>Quantitative T₂ maps using the EMC matching algorithm detected consistent changes in KAC T₂ values after a short walking period.</div></div><div><h3>Implications for practice</h3><div>EMC quantitative T2 maps effectively detected knee cartilage changes post-walking. This technique could improve cartilage hydration assessments, aiding early detection in at-risk patients. It also suggests potential for personalized monitoring and rehabilitation, advancing musculoskeletal imaging and non-invasive joint health monitoring.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 1","pages":"Pages 66-74"},"PeriodicalIF":2.5,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142630389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Features of and barriers to effective teamwork at university and on clinical placement: The student radiographer perspective","authors":"L. Monks,&nbsp;S. Mackay","doi":"10.1016/j.radi.2024.10.015","DOIUrl":"10.1016/j.radi.2024.10.015","url":null,"abstract":"<div><h3>Introduction</h3><div>Radiography departments require effective teamwork in order to deliver high standards of safe and efficient patient care.</div><div>The aim of this study was to explore the features of and barriers to effective teamwork as experienced by pre-registration BSc and MSc diagnostic radiography students at university and during clinical placement.</div></div><div><h3>Method</h3><div>This qualitative study used semi-structured interviews and the thematic analysis approach of Braun and Clark to investigate the views of diagnostic radiography students on BSc and MSc pre-registration programmes from one university in the Northwest of England.</div></div><div><h3>Results</h3><div>Barriers to teamwork were identified in a main theme, <em>acceptance into the team</em> and two subthemes, <em>theory-practice gap</em> and <em>trying on the professional self</em>. Features of effective teams were identified in two main themes, <em>positive experiences of teamwork</em> and <em>an ideal team</em>. Students highlighted caring for the team, as equally as important as caring for the patient, and another main theme, <em>a caring team</em>, described both the barriers to, and features of, effective teams.</div></div><div><h3>Conclusion</h3><div>Students had a developed understanding of the features of effective teams and equated a team that cares for each other, as one able to provide the best care to patients. This study provides an insight into the impact of teamwork on radiography students experiences of university and clinical placement. Barriers to teamwork affect students’ sense of belonging and overall professional development in a clinical environment.</div></div><div><h3>Implications for practice</h3><div>This study can better inform university and clinical staff regarding improvements to teamworking education and practice for students. It may also provide insights which may influence the teamworking practice of clinical staff.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"30 ","pages":"Pages 88-95"},"PeriodicalIF":2.5,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142606226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can radiographer regulatory compliance contribute to patient safety in the emergency department fast-track pathway? A retrospective pilot study","authors":"B. Pearce ,&nbsp;S. Uribe ,&nbsp;C. Cowling ,&nbsp;J.-A. Pinson ,&nbsp;W. Smith ,&nbsp;J. Sim","doi":"10.1016/j.radi.2024.10.014","DOIUrl":"10.1016/j.radi.2024.10.014","url":null,"abstract":"<div><h3>Introduction</h3><div>Radiographers in clinical imaging pathways ensure regulatory compliance by justifying X-ray requests, optimising exposure, and communicating urgent findings. In Australia, adherence to Australian regulatory directives is crucial for patient safety, particularly in Emergency Departments (EDs) where immediate radiologist report or guidance may be unavailable. This study explores whether Australian radiographers working within regulatory compliance of justification, optimisation and Preliminary Image Evaluation (PIE) in the ED contribute to improving patient safety?</div></div><div><h3>Methods</h3><div>In a retrospective blinded single-phase study, 28 radiographers reviewed 50 cases of single extremity trauma in the ED Fast-Track (FT) pathway. Data analysis assessed compliance with regulatory directives, evaluating justification, optimisation, and accuracy of Preliminary Image Evaluations (PIE) against established standards.</div></div><div><h3>Results</h3><div>Justification: Radiographers found 67.8 % (n = 881) of X-ray requests compliant and 32.2 % (n = 419) non-compliant. Optimisation: Participants optimised referrals by correcting anatomical selection (52.0 %, n = 676), adjusting the number of images (11.6 %, n = 151), or both (17.5 %, n = 227). PIE: Radiographer PIE demonstrated a mean sensitivity of 94.7 % (CI: 92.9 %–96.6 %), specificity of 89.6 % (CI: 87.0 %–92.2 %), and accuracy of 92.7 % (CI: 91.6 %–93.8 %). The average Positive Predictive Value (PPV) was 93.2 % (CI: 92.0–94.9 %), the Negative Predictive Value (NPV) was 91.9 % (CI: 90.2–95.0 %), and Cohen’s Kappa inter-rater reliability median was K = 0.85, with an average result of K = 0.85 (range: K = 0.74 to K = 0.96).</div></div><div><h3>Conclusion</h3><div>In this study, radiographer compliance with regulatory standards for justification, optimisation, and PIE is high but not fully consistent. When radiographers adhere to regulations, there is potential to improve patient safety. Collaborative compliance between radiologists, referrers, and radiographers within the ED FT pathway could further improve patient safety outcomes. Additional research, including prospective studies, is necessary to further evaluate radiographer compliance in the ED FT pathway.</div></div><div><h3>Implications for practice</h3><div>Radiographers are professionally obligated to follow Australian regulatory directives for safe medical radiation practice, guided by imaging protocols. Timely and accurate PIE by radiographers can enhance patient safety in ED.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 1","pages":"Pages 53-65"},"PeriodicalIF":2.5,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142630388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A tutor training framework for radiographers: Basic concepts to effectively train future generations of professionals","authors":"E. Scaramelli ,&nbsp;G.R. Bonfitto ,&nbsp;A. Roletto ,&nbsp;L. Bombelli ,&nbsp;S.V. Fasulo ,&nbsp;D. Catania","doi":"10.1016/j.radi.2024.10.023","DOIUrl":"10.1016/j.radi.2024.10.023","url":null,"abstract":"<div><h3>Introduction</h3><div>Clinical practice is crucial for the professional development of radiographers. To effectively benefit from their training, students need guidance from well-trained and competent tutors. However, the literature lacks evidence of training programs specifically designed for radiographer tutors. This study aims to suggest a novel framework able to identify the key elements of a successful tutor training curriculum for radiographers.</div></div><div><h3>Methods</h3><div>Through a literature review on the topic of tutor training in the healthcare sector, a novel tutor training framework specifically for radiographers was developed. This model is structured into two main components: <em>knowledge development</em> and <em>skill acquisition</em>. The framework emphasizes four key topics: understanding the essence of tutoring; conducting briefing, debriefing, and providing feedback; addressing students' psychosocial challenges; conducting simulations and role plays. It concludes with a skill test.</div></div><div><h3>Results</h3><div>The proposed curriculum highlights the importance of tutors understanding their roles and responsibilities, as well as the significance of providing feedback and conducting briefing activities. Noteworthy additions to this pioneering model include an in-depth examination of the psychosocial challenges faced by students during their training and the introduction of role-playing activities. These activities help tutors develop empathy and better understand the students' perspectives and needs, therefore optimizing the tutoring experience.</div></div><div><h3>Conclusion</h3><div>This framework outlines the fundamental principles that tutors should incorporate into their daily tutoring activities to maximize student learning and engagement. Emphasis is placed on understanding the psychological challenges faced by students, which can help tutors tailor their teaching to better meet students' needs.</div></div><div><h3>Implication for practice</h3><div>The proposed framework wills to promote significant improvement in the clinical practice of future professionals through the optimization of tutors' competencies.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"30 ","pages":"Pages 96-103"},"PeriodicalIF":2.5,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142630385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT metal artefact reduction for hip and shoulder implants using novel algorithms and machine learning: A systematic review with pairwise and network meta-analyses","authors":"K. Amadita,&nbsp;F. Gray,&nbsp;E. Gee,&nbsp;E. Ekpo,&nbsp;Y. Jimenez","doi":"10.1016/j.radi.2024.10.009","DOIUrl":"10.1016/j.radi.2024.10.009","url":null,"abstract":"<div><h3>Introduction</h3><div>Many tools have been developed to reduce metal artefacts in computed tomography (CT) images resulting from metallic prosthesis; however, their relative effectiveness in preserving image quality is poorly understood. This paper reviews the literature on novel metal artefact reduction (MAR) methods targeting large metal artefacts in fan-beam CT to examine their effectiveness in reducing metal artefacts and effect on image quality.</div></div><div><h3>Methods</h3><div>The PRISMA checklist was used to search for articles in five electronic databases (MEDLINE, Scopus, Web of Science, IEEE, EMBASE). Studies that assessed the effectiveness of recently developed MAR method on fan-beam CT images of hip and shoulder implants were reviewed. Study quality was assessed using the National Institute of Health (NIH) tool. Meta-analyses were conducted in R, and results that could not be meta-analysed were synthesised narratively.</div></div><div><h3>Results</h3><div>Thirty-six studies were reviewed. Of these, 20 studies proposed statistical algorithms and 16 used machine learning (ML), and there were 19 novel comparators. Network meta-analysis of 19 studies showed that Recurrent Neural Network MAR (RNN-MAR) is more effective in reducing noise (LogOR 20.7; 95 % CI 12.6–28.9) without compromising image quality (LogOR 4.4; 95 % CI -13.8-22.5). The network meta-analysis and narrative synthesis showed novel MAR methods reduce noise more effectively than baseline algorithms, with five out of 23 ML methods significantly more effective than Filtered Back Projection (FBP) (<em>p</em> &lt; 0.05). Computation time varied, but ML methods were faster than statistical algorithms.</div></div><div><h3>Conclusion</h3><div>ML tools are more effective in reducing metal artefacts without compromising image quality and are computationally faster than statistical algorithms. Overall, novel MAR methods were also more effective in reducing noise than the baseline reconstructions.</div></div><div><h3>Implications for practice</h3><div>Implementation research is needed to establish the clinical suitability of ML MAR in practice.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 1","pages":"Pages 36-52"},"PeriodicalIF":2.5,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical insights into cross-sectional imaging integration in radiography education","authors":"M. Friel ,&nbsp;R. Young ,&nbsp;M.F. McEntee ,&nbsp;M. Rawashdeh ,&nbsp;A. England","doi":"10.1016/j.radi.2024.10.019","DOIUrl":"10.1016/j.radi.2024.10.019","url":null,"abstract":"<div><h3>Introduction</h3><div>Clinical practice is a critical component of radiography curricula, offering students with essential skills and training for proficient practice. Educational institutions are challenged to review and develop strategies to meet evolving service demands regularly. This study aims to gain insight into the inclusion of cross-sectional imaging within pre-registration radiography training.</div></div><div><h3>Methods</h3><div>An online questionnaire, based on previous European Federation of Radiographer Societies (EFRS) surveys, included closed-ended questions and ascertained the level of qualification, cross-sectional imaging incorporation, and tasks and assessments within programmes. The questionnaire was distributed through the EFRS Research Hub at the European Congress of Radiology (ECR) 2023 and online via social media. Closed-ended questions were summarised using descriptive statistics.</div></div><div><h3>Results</h3><div>Responses were received from 64 individual radiography educators across 29 different countries. Fifty-seven respondents (91.9 %) reported including cross-sectional imaging training in their institution's pre-registration radiography programme. An increase in the amount of time dedicated to clinical training in cross-sectional imaging was reported by 24 respondents (42.1 %). Overall, 32 individuals (53.3 %) stated that CT is a specialised modality, and dedicated training should be for radiographers once they obtain their basic qualifications. In contrast, 36 respondents (61 %) agreed that MRI should also be reserved as a specialised modality.</div></div><div><h3>Conclusion</h3><div>Study findings indicate a lack of consistency among pre-registration radiography programmes in terms of how they include cross-sectional imaging in their curricula. Differing opinions on this issue are likely to be guided by national standards and workforce requirements upon qualification.</div></div><div><h3>Implications for practice</h3><div>Variations in training curricula can present significant challenges for graduates. To align with the most recent Standards of Proficiency, curricula must be regularly reviewed and updated. Such Standards now typically require radiographers to perform a range of CT scans, including those of the head, C-spine, chest, and abdomen. Therefore, integrating comprehensive training in cross-sectional imaging into pre-registration education is crucial to ensure that future professionals meet these essential competencies and are fully prepared for their roles.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 1","pages":"Pages 20-26"},"PeriodicalIF":2.5,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Paediatric diagnostic reference levels for common computed tomography procedures: A systematic review","authors":"I. Garba ,&nbsp;P. Engel-Hills","doi":"10.1016/j.radi.2024.09.058","DOIUrl":"10.1016/j.radi.2024.09.058","url":null,"abstract":"<div><h3>Background</h3><div>Previous paediatric diagnostic reference levels (PDRL) literature reviews for commonly performed procedures of the brain, chest and abdomen revealed wide DRL variation and deviation of scanning protocols across CT centres. The current review went further to determine the extent and possible factors of DRL variation in the same procedure, age or weight group, between scanners and CT centres for the standardisation of CT practice globally.</div></div><div><h3>Methods</h3><div>The preferred reporting items for systematic reviews and meta-analysis (PRISMA) flow chart was used to screen articles in Science Direct, Medline, Academic Search Complete via EBSCOhost, PubMed, and CINAHL via EBSCOhost including the Google search engine.</div></div><div><h3>Results</h3><div>A total of 6573 articles were retrieved and screened against the established criteria and finally, 52 articles were selected and synthesised narratively.</div></div><div><h3>Conclusion</h3><div>The findings of this review show variation of brain PDRLs up to a factor of 2 fold for the same examination and age group. Factors attributable to dose variations noted in this review were largely related to the setting of the scan protocols such as the use of different phantom sizes, dose parameters, and age groups. This indicates the need to standardise methods of establishing PDRLs and alignment with the European Commission and ICRP recommended guidelines are proposed.</div></div><div><h3>Implication for practice</h3><div>The review highlights different methods for establishing PDRLs and their implication which could guide radiographers and medical physicists in future PDRLs establishment for dose optimization.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 1","pages":"Pages 27-35"},"PeriodicalIF":2.5,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142591935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"“Making it work in the face of extreme adversity” - Exploring perceptions for the future of the imaging and oncology workforce using ‘soundbite’ interviews","authors":"J. Harcus,&nbsp;G. Ferrari,&nbsp;E. Berry,&nbsp;E. Cadogan,&nbsp;C.S. McNally,&nbsp;A. Bardwell,&nbsp;N. Singh,&nbsp;J. Beck","doi":"10.1016/j.radi.2024.10.017","DOIUrl":"10.1016/j.radi.2024.10.017","url":null,"abstract":"<div><h3>Background</h3><div>Public demand and scrutiny, an aging population, inefficient funding and the legacy of Covid-19 are just some of the challenges the United Kingdom's health service faces. In imaging and oncology, there has been an exponential growth in service need against a workforce which is struggling to recruit and retain. This project aims to explore what the current, and future, workforce perceive the main opportunities and solutions, threats and risks are.</div></div><div><h3>Method</h3><div>Very short structured ‘soundbite’ interviews were employed to capture brief opinions or ‘snippets’ of dialogue. Participants recruited at a large imaging and oncology congress were asked what they considered the most significant opportunity/solution and threat/risk related to the future workforce. Descriptive and content analysis was undertaken to provide evaluation of role, regions, and frequency of themes.</div></div><div><h3>Results</h3><div>88 ‘soundbite’ interviews were undertaken lasting between 30 s and 4 min in length. The most common themes relating to opportunities/solutions considered education and students, workforce development and skill mix, and the use of technology. The most common threats/risks were identified as a lack of support for the workforce, recruitment and retention, national strategic issues, and barriers to workforce development.</div></div><div><h3>Conclusion</h3><div>The current workforce perceives a greater number of threats/risks for the future than potential opportunities/solutions. In particular, burnout and staff attrition were the most frequent perceptions of risk, though role development was often highlighted as the biggest opportunity. Interestingly AI and technology were frequently considered both opportunity and threat.</div></div><div><h3>Implications for practice</h3><div>This study highlights that a lot needs to be done to support our future workforce and make best use of the potential opportunities and solutions.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 1","pages":"Pages 12-19"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142563778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors of importance for the development of evidence-based practice amongst radiographers in public healthcare","authors":"A. Bolejko ,&nbsp;B.R. Mussmann ,&nbsp;J. Debess ,&nbsp;A. Henner ,&nbsp;A. Sanderud ,&nbsp;B.T. Andersson ,&nbsp;E. Saukko ,&nbsp;K. Fridell","doi":"10.1016/j.radi.2024.10.011","DOIUrl":"10.1016/j.radi.2024.10.011","url":null,"abstract":"<div><h3>Introduction</h3><div>Research evidence suggests that radiographers often rely on previous training, traditional practices, work experience and protocols developed within the department rather than up-to-date research-based evidence in their daily practice. The aim of the study was to investigate factors that might impact the development of evidence-based practice amongst radiographers in clinical public settings in the Nordic countries.</div></div><div><h3>Methods</h3><div>An online survey was performed amongst 640 radiographers in four Nordic countries. Multivariate logistic regression was performed to investigate the odds ratio (OR) of facilitators for and barriers to radiographers' development of evidence-based practice.</div></div><div><h3>Results</h3><div>A reflective approach in everyday practice and being aware of the current research evidence were significant facilitators for radiographers' development of evidence-based practice (OR ≥ 3.10, p &lt; 0.001). Discussing research with colleagues and managers was associated with engagement in the utilisation of evidence (OR 7.21, p &lt; 0.001). Difficulties in evaluating research evidence represented the only significant barrier (OR 1.84, p 0.009).</div></div><div><h3>Conclusion</h3><div>A critical approach amongst radiographers in their performance of healthcare in diagnostic imaging, and the development of their academic skills to improve awareness of the available research evidence are important factors for developing evidence-based practice in radiography. Leadership is crucial for the engagement of radiographers in the development of evidence-based practice. Management should facilitate the development of a learning culture within diagnostic imaging.</div></div><div><h3>Implications for practice</h3><div>The results provide suggestions for the development of a learning culture, proactive and person-centred leadership, and strategic management for the provision of research infrastructure, all of which contribute to the further integration of evidence-based practice in radiography. Also, the study results suggest the importance of shared responsibility for creating a critical fellowship in diagnostic imaging.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 1","pages":"Pages 1-5"},"PeriodicalIF":2.5,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiographer Education and Learning in Artificial Intelligence (REAL-AI): A survey of radiographers, radiologists, and students’ knowledge of and attitude to education on AI","authors":"G. Doherty ,&nbsp;L. McLaughlin ,&nbsp;C. Hughes ,&nbsp;J. McConnell ,&nbsp;R. Bond ,&nbsp;S. McFadden","doi":"10.1016/j.radi.2024.10.010","DOIUrl":"10.1016/j.radi.2024.10.010","url":null,"abstract":"<div><h3>Introduction</h3><div>In Autumn 2023, amendments to the Health and Care Professions Councils (HCPC) Standards of Proficiency for Radiographers were introduced requiring clinicians to demonstrate awareness of the principles of AI and deep learning technology, and its application to practice’ (HCPC 2023; standard 12.25). With the rapid deployment of AI in departments, staff must be prepared to implement and utilise AI. AI readiness is crucial for adoption, with education as a key factor in overcoming fear and resistance. This survey aimed to assess the current understanding of AI among students and qualified staff in clinical practice.</div></div><div><h3>Methods</h3><div>A survey targeting radiographers (diagnostic and therapeutic), radiologists and students was conducted to gather demographic data and assess awareness of AI in clinical practice. Hosted online via JISC, the survey included both closed and open-ended questions and was launched in March 2023 at the European Congress of Radiology (ECR).</div></div><div><h3>Results</h3><div>A total of 136 responses were collected from participants across 25 countries and 5 continents. The majority were diagnostic radiographers 56.6 %, followed by students 27.2 %, dual-qualified 3.7 % and radiologists 2.9 %. Of the respondents, 30.1 % of respondents indicated that their highest level of qualification was a Bachelor's degree, 29.4 % stated that they are currently using AI in their role, whilst 27 % were unsure. Only 10.3 % had received formal AI training.</div></div><div><h3>Conclusion</h3><div>This study reveals significant gaps in training and understanding of AI among medical imaging staff. These findings will guide further research into AI education for medical imaging professionals.</div></div><div><h3>Implications for practice</h3><div>This paper lays foundations for future qualitative studies on the provision of AI education for medical imaging professionals, helping to prepare the workforce for the evolving role of AI in medical imaging.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"30 ","pages":"Pages 79-87"},"PeriodicalIF":2.5,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}